Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Ti3C2Tx Composite Aerogels Enable Pressure Sensors for Dialect Speech Recognition Assisted by Deep Learning

作者:Yanan Xiao, He Li, Tianyi Gu, Xiaoteng Jia, Shixiang Sun, Yong Liu, Bin Wang, He Tian, Peng Sun, Fangmeng Liu, Geyu Lu · 发表于:Nano-Micro Letters · 年份:2024 · DOI:10.1007/s40820-024-01605-z · 被引用次数:39 · 研究领域:MXene and MAX Phase Materials、Advanced Sensor and Energy Harvesting Materials、Advanced Thermoelectric Materials and Devices

Abstract Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection. However, current intelligent speech assistants based on pressure sensors can only recognize standard languages, which hampers effective communication for non-standard language people. Here, we prepare an ultralight Ti 3 C 2 T x MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 kPa, rapid response/recovery time, and low hysteresis (13.69%). The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference, allowing for accurate recognition of six dialects (96.2% accuracy) and seven different words (96.6% accuracy) with the assistance of convolutional neural networks. This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.